In insurance claim processing, there is a need to define different claim handling processes for different codes used for medical procedures or drug prescriptions. One of the most widely used coding systems is the “International Statistical Classification of Diseases and Related Health Problems” (ICD) published by the World Health Organization. ICD provides codes to classify diseases and a wide variety of signs, symptoms, abnormal findings, complaints, social circumstances, and external causes of injury or disease. Under this system, every health condition can be assigned to a unique category and given a code. Such categories can include a set of similar diseases.
The use of ICD codes is mandated by law in many countries. In the United States, for example, ICD's 9th revision (ICD-9) has been the mandated coding standard for health insurance claims, including Medicare claims, since 1988. In the currently used claim processing methods, the codes are often stored in tables or groups. The number of tables is in the order of tens of thousands. The number of codes covered by each table varies and can be in the order of thousands. If the codes for a group of related procedures or diagnosis are sequential, the tables may be implemented to group the codes in predefined ranges. Setting a range as defined by a table saves computation time during a search, because it reduces the sizes of the tables (allowing more tables and their contents to be stored in memory and CPU caches) and because fewer operations are necessary to search a smaller table.
Due to the nature of the codes in the ICD-9 code sets, the above approach has been mostly useful for processing related claims. However, ICD-9 is to be replaced with the ICD-10 code sets effective Oct. 1, 2013. Industry experts expect that the above-noted grouping approach may be unsuitable for ICD-10 because the code implementation in ICD-10 is scattered in a way that use of ranges may result in creating large code tables that are inefficient for the purpose of searching. Certain methods, such as entry compression, encoding or clustering are available that may help reduce the size of the tables. Such solutions, never-the-less, result in an increase in search time.